taskflow/taskflow/examples/dump_memory_backend.py

73 lines
2.1 KiB
Python

# -*- coding: utf-8 -*-
# Copyright (C) 2015 Yahoo! Inc. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License"); you may
# not use this file except in compliance with the License. You may obtain
# a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS, WITHOUT
# WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the
# License for the specific language governing permissions and limitations
# under the License.
import logging
import os
import sys
logging.basicConfig(level=logging.ERROR)
self_dir = os.path.abspath(os.path.dirname(__file__))
top_dir = os.path.abspath(os.path.join(os.path.dirname(__file__),
os.pardir,
os.pardir))
sys.path.insert(0, top_dir)
sys.path.insert(0, self_dir)
from taskflow import engines
from taskflow.patterns import linear_flow as lf
from taskflow import task
# INTRO: in this example we create a dummy flow with a dummy task, and run
# it using a in-memory backend and pre/post run we dump out the contents
# of the in-memory backends tree structure (which can be quite useful to
# look at for debugging or other analysis).
class PrintTask(task.Task):
def execute(self):
print("Running '%s'" % self.name)
# Make a little flow and run it...
f = lf.Flow('root')
for alpha in ['a', 'b', 'c']:
f.add(PrintTask(alpha))
e = engines.load(f)
e.compile()
e.prepare()
# After prepare the storage layer + backend can now be accessed safely...
backend = e.storage.backend
print("----------")
print("Before run")
print("----------")
print(backend.memory.pformat())
print("----------")
e.run()
print("---------")
print("After run")
print("---------")
for path in backend.memory.ls_r(backend.memory.root_path, absolute=True):
value = backend.memory[path]
if value:
print("%s -> %s" % (path, value))
else:
print("%s" % (path))